STaT: Resolving Shape Distortion in Non-Stationary Time Series via Tri-Modal Synergy

ArXi:2605.25943v1 Announce Type: new Recent research in time series forecasting frequently investigates the integration of textual and visual modalities with numerical models to better navigate non-stationary environments. Despite delivering solid numerical results, existing multi-modal approaches usually encounter a dilemma: prioritizing the minimization of average errors can result in excessively smooth forecasts that overlook essential fluctuations. To resolve this limitation, we